activity
20162024
most citedGrounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)

30 citations · 68 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2024★ 30 cited

Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)

Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly

With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes domains, ensuring the trustworthiness, safety, and observability of these systems has b…

cs.SI2023★ 23 cited

Social network modeling and applications, a tutorial

Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…

cs.CV2020

Explainable Deep Classification Models for Domain Generalization

Andrea Zunino, Sarah Adel Bargal, Riccardo Volpi +5

Conventionally, AI models are thought to trade off explainability for lower accuracy. We develop a training strategy that not only leads to a more explainable AI system for object…

cs.HC2019★ 3 cited

BUOCA: Budget-Optimized Crowd Worker Allocation

Mehrnoosh Sameki, Sha Lai, Kate K. Mays +3

Due to concerns about human error in crowdsourcing, it is standard practice to collect labels for the same data point from multiple internet workers. We here show that the resultin…

cs.CV2017

Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)

Danna Gurari, Kun He, Bo Xiong +6

We propose the ambiguity problem for the foreground object segmentation task and motivate the importance of estimating and accounting for this ambiguity when designing vision syste…

cs.HC2016★ 4 cited

Dynamic Allocation of Crowd Contributions for Sentiment Analysis during the 2016 U.S. Presidential Election

Mehrnoosh Sameki, Mattia Gentil, Kate K. Mays +2

Opinions about the 2016 U.S. Presidential Candidates have been expressed in millions of tweets that are challenging to analyze automatically. Crowdsourcing the analysis of politica…

cs.CV2016★ 8 cited

Salient Object Subitizing

Jianming Zhang, Shugao Ma, Mehrnoosh Sameki +6

We study the problem of Salient Object Subitizing, i.e. predicting the existence and the number of salient objects in an image using holistic cues. This task is inspired by the abi…